Internal change.

PiperOrigin-RevId: 446058586
jagadeeshi2i · May 11, 2022 · e453fe3 · e453fe3
1 parent 34b5d0b
commit e453fe3
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diff --git a/...nts/google-cloud/google_cloud_pipeline_components/experimental/automl/tabular/__init__.py b/...nts/google-cloud/google_cloud_pipeline_components/experimental/automl/tabular/__init__.py
@@ -21,10 +21,19 @@
   from kfp.components import load_component_from_file
 
 __all__ = [
-    'CvTrainerOp', 'InfraValidatorOp', 'Stage1TunerOp', 'EnsembleOp',
-    'StatsAndExampleGenOp', 'FeatureSelectionOp', 'TransformOp', 'FinalizerOp',
-    'WideAndDeepTrainerOp', 'BuiltinAlgorithmHyperparameterTuningJobOp',
-    'TabNetTrainerOp', 'FeatureTransformEngineOp'
+    'CvTrainerOp',
+    'InfraValidatorOp',
+    'Stage1TunerOp',
+    'EnsembleOp',
+    'StatsAndExampleGenOp',
+    'FeatureSelectionOp',
+    'TransformOp',
+    'FinalizerOp',
+    'WideAndDeepTrainerOp',
+    'BuiltinAlgorithmHyperparameterTuningJobOp',
+    'TabNetTrainerOp',
+    'FeatureTransformEngineOp',
+    'FteTransformConfigurationOp',
 ]
 
 CvTrainerOp = load_component_from_file(
@@ -43,6 +52,10 @@
     os.path.join(os.path.dirname(__file__), 'transform.yaml'))
 FeatureTransformEngineOp = load_component_from_file(
     os.path.join(os.path.dirname(__file__), 'feature_transform_engine.yaml'))
+FteTransformConfigurationOp = load_component_from_file(
+    os.path.join(
+        os.path.dirname(__file__),
+        'feature_transform_engine_transform_configuration.yaml'))
 FinalizerOp = load_component_from_file(
     os.path.join(os.path.dirname(__file__), 'finalizer.yaml'))
 WideAndDeepTrainerOp = load_component_from_file(

diff --git a/...ponents/experimental/automl/tabular/feature_transform_engine_transform_configuration.yaml b/...ponents/experimental/automl/tabular/feature_transform_engine_transform_configuration.yaml
@@ -0,0 +1,71 @@
+# Copyright 2021 The Kubeflow Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+name: feature_transform_engine_transform_configuration
+description: |
+  Generates an Fte transform configuration for our dataset when not specified by the user.
+
+    Args:
+        project (str):
+            Required. Project to run Fte transform configuration
+        location (Optional[str]):
+            Location for running the te transform configuration. If not set, default to us-central1
+        root_dir (str): The Cloud Storage location to store the output.
+        metadata_path (str): The metadata of the dataset
+        dataset_stats_path (str): The dataset stats of the dataset
+        encryption_spec_key_name (Optional[str]):
+            Customer-managed encryption key
+
+    Returns:
+        fte_transform_configuration_artifact_path (str): The path to the  fte transform configutation path.
+        gcp_resources (str):
+            GCP resources created by this component.
+            For more details, see https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/proto/README.md.
+inputs:
+- {name: project, type: String}
+- {name: location, type: String, optional: True, default: "us-central1"}
+- {name: root_dir, type: String}
+- {name: metadata_path, type: String}
+- {name: dataset_stats_path, type: String}
+- {name: encryption_spec_key_name, type: String, default: ""}
+
+outputs:
+- {name: fte_transform_configuration_artifact_path, type: String}
+- {name: gcp_resources, type: String}
+
+implementation:
+  container:
+    image: gcr.io/ml-pipeline/google-cloud-pipeline-components:latest
+    command: [python3, -u, -m, google_cloud_pipeline_components.container.v1.gcp_launcher.launcher]
+    args: [
+      --type, CustomJob,
+      --project, {inputValue: project},
+      --location, {inputValue: location},
+      --gcp_resources, {outputPath: gcp_resources},
+      --payload,
+      concat: [
+        '{"display_name": "automl-tabular-transform-{{$.pipeline_job_uuid}}-{{$.pipeline_task_uuid}}", "encryption_spec": {"kms_key_name":"',
+        {inputValue: encryption_spec_key_name},
+        '"}, "job_spec": {"worker_pool_specs": [{"replica_count": 1, "machine_spec": {"machine_type": "n1-standard-8"}, "container_spec": {"image_uri":"',
+        'us-docker.pkg.dev/vertex-ai-restricted/automl-tabular/training:prod',
+        '", "args": ["transform_configuration", "--fte_transform_configuration_artifact_path=',
+        {outputPath: fte_transform_configuration_artifact_path},
+        '", "--fte_transform_configuration_path=',
+        {inputValue: root_dir},
+        '/{{$.pipeline_job_uuid}}/{{$.pipeline_task_uuid}}/transform_configuration", "--metadata_path=',
+        {inputValue: metadata_path},
+        '", "--dataset_stats_path=',
+        {inputValue: dataset_stats_path},
+        '"]}}]}}'
+      ]]